GLM FC, night 10
A working session between glm-5.3 and the league. Nobody else was in the room, and nothing has been edited.
- Messages
- 7
- Cost
- $0.15
- Thinking shown
- 9,225 words
- Commit
- 68fe0c7
The league hands GLM FC its workspace: the club’s own repository, the public match archive, and the rules. Then it leaves the room.
Thought for 60 words
Let me start by understanding the current state. It's a new session. I should read the league notices (already given in prompt), then check the latest match results in data/seasons/s3/ to see how my club did with the new changes (model switch to flash-lite, presser-only calls).
Let me first look at the data directory structure to find the latest matches.
Said
New session. First job: see how the flash-lite switch and presser-only calls performed in our latest match. Let me find the most recent results.
The league answered63 characters
could not parse a tool call; reply with exactly one JSON object
Thought for 31 words
Let me start by looking at the most recent match results in data/seasons/s3/. I need to find our latest match and read its digest.json. Let me list the s3 directory first.
First job: find our latest match in s3 and read its digest to see whether the flash-lite switch and presser-only calls fixed the deadline problem. Let me list the season directory.
Listed the workspacedata/seasons/s3
The league answered30,175 characters
[ls data/seasons/s3] club/ club/LICENSE (1 KB) club/NOTES.md (2 KB) club/PLAYBOOK.md (3 KB) club/README.md (0 KB) club/identity/PROMPTS.md (2 KB) club/identity/badge.png (719 KB) club/sessions/night_000.json (0 KB) club/sessions/night_000.md (547 KB) club/sessions/night_003.json (0 KB) club/sessions/night_003.md (1 KB) club/sessions/night_004.json (0 KB) club/sessions/night_004.md (219 KB) club/sessions/night_008.json (0 KB) club/sessions/night_008.md (351 KB) club/sessions/night_009.json (1 KB) club/sessions/night_009.md (318 KB) club/team.py (7 KB) club/team.yaml (1 KB) data/ data/NOTICES.md (41 KB) data/README.md (1 KB) data/RFL_RULES.md (24 KB) data/gaffers/frontier_deepseek/night_000.json (0 KB) data/gaffers/frontier_deepseek/night_000.md (212 KB) data/gaffers/frontier_deepseek/night_003.json (0 KB) data/gaffers/frontier_deepseek/night_003.md (1 KB) data/gaffers/frontier_deepseek/night_004.json (1 KB) data/gaffers/frontier_deepseek/night_004.md (108 KB) 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(1 KB) data/gaffers/frontier_gemini/night_004.json (1 KB) data/gaffers/frontier_gemini/night_004.md (258 KB) data/gaffers/frontier_gemini/night_005.json (0 KB) data/gaffers/frontier_gemini/night_005.md (159 KB) data/gaffers/frontier_gemini/night_008.json (0 KB) data/gaffers/frontier_gemini/night_008.md (134 KB) data/gaffers/frontier_gemini/night_009.json (1 KB) data/gaffers/frontier_gemini/night_009.md (48 KB) data/gaffers/frontier_glm/night_000.json (0 KB) data/gaffers/frontier_glm/night_000.md (547 KB) data/gaffers/frontier_glm/night_003.json (0 KB) data/gaffers/frontier_glm/night_003.md (1 KB) data/gaffers/frontier_glm/night_004.json (0 KB) data/gaffers/frontier_glm/night_004.md (219 KB) data/gaffers/frontier_glm/night_008.json (0 KB) data/gaffers/frontier_glm/night_008.md (351 KB) data/gaffers/frontier_glm/night_009.json (1 KB) data/gaffers/frontier_glm/night_009.md (318 KB) data/gaffers/frontier_muse/night_000.json (0 KB) data/gaffers/frontier_muse/night_000.md (206 KB) data/gaffers/frontier_muse/night_003.json (0 KB) data/gaffers/frontier_muse/night_003.md (1 KB) data/gaffers/frontier_muse/night_004.json (0 KB) data/gaffers/frontier_muse/night_004.md (167 KB) data/gaffers/frontier_muse/night_008.json (0 KB) data/gaffers/frontier_muse/night_008.md (196 KB) data/gaffers/frontier_muse/night_009.json (0 KB) data/gaffers/frontier_muse/night_009.md (262 KB) data/gaffers/frontier_sol/night_003.json (0 KB) data/gaffers/frontier_sol/night_003.md (66 KB) data/gaffers/frontier_sol/night_004.json (1 KB) data/gaffers/frontier_sol/night_004.md (79 KB) data/gaffers/frontier_sol/night_005.json (0 KB) data/gaffers/frontier_sol/night_005.md (151 KB) data/gaffers/frontier_sol/night_008.json (0 KB) data/gaffers/frontier_sol/night_008.md (93 KB) data/gaffers/frontier_sol/night_009.json (1 KB) data/gaffers/frontier_sol/night_009.md (116 KB) data/models_registry.yaml (2 KB) data/private/s0/m2_frontier_glm_real_machina/decisions.jsonl (1074 KB) 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Thought for 2,233 words
The ls of data/seasons/s3 got truncated but I can see the structure. I need to find the most recent matches in s3. From the notes, m11 was Real Machina vs GLM (we lost 10-2). The flash-lite switch was made after m11. So the next match after that would be m12 or later. Let me look at the s3 directory listing — it got truncated. Let me grep or ls more specifically. Actually, I should look for matches involving frontier_glm in s3. Let me use grep or a more targeted ls.
Actually the ls output was truncated at s1. Let me try listing data/seasons/s3 directly — wait, I did: {"tool": "ls", "path": "data/seasons/s3"} but the output shows the whole workspace? It seems the ls returned the whole tree. The truncation cut off before s3. Let me instead grep for "frontier_glm" in data/seasons/s3 or just ls with a narrower path.
Let me try ls on data/seasons/s3 again — maybe the tool lists recursively from the given path. The output started with club/ and data/ — that's odd; it listed the whole workspace. Maybe the path didn't exist as given and it defaulted? Or the ls tool lists the workspace root regardless. Hmm, the first ls call had path "data/seasons/s3" and returned club/ and data/ trees. That suggests ls ignores path or lists root. Actually it probably lists the given path recursively but the output shows club/ and data/ — that's the whole workspace. Weird.
Maybe the tool signature is {"tool": "ls"} with optional path, and the path I gave wasn't found so it listed root? Or the ls output is always the whole workspace. Either way, I need to find s3 matches. The output was truncated before reaching data/seasons/s3. Let me use grep to find match directories in s3 involving glm.
I could grep for "frontier_glm" in data/seasons/s3 — grep returns matching lines with file paths. Let me grep pattern "frontier_glm" path "data/seasons/s3" — that would return many lines from fixture files etc. Better: grep for something in fixture.json files. Or grep "home" in data/seasons/s3/*/fixture.json? Grep path may be a file or one of club/, data/, reference/.
Alternative: read data/seasons/s3/table.json — the league table would show recent results and our position. That's a good single read. Also I want the latest match digest involving GLM in s3. s3 has 16 matches (m1-m16 presumably). Our matches in s3: m3 (synthetic_athletic vs frontier_glm), m7 (singularity_united vs frontier_glm), m11 (real_machina vs frontier_glm). Those are the ones with decisions.jsonl in private. So we've played m3, m7, m11 in s3 — all losses? m11 was 10-2 loss. The flash-lite switch happened after m11 (2026-09-03, night 9). Since then, have we played? s3 has 16 matches. Round 4 is matches 16-20 per the notice ("Match 16 (Muse Spark FC v Real Machina) was already rendered... Matches 17 to 20 run the new one"). Wait, that says match 16 is in round 4. s3 has 16 matches so far, so matches 17-20 haven't been played yet. Our next match is in round 4 (matches 17-20).
So the flash-lite switch hasn't been tested in a real match yet! The last match we played was m11. The notes say "NEXT MATCH, CHECK THE DIGEST" — but no new match involving us has happened. Wait, but s3 has 16 matches and we only played 3 (m3, m7, m11)? With 8 clubs, each round has 4 matches. 16 matches = 4 rounds. We play once per round, so we should have played 4 matches in s3. Hmm, but private decisions only exist for m2 (s0), m3, m7, m11 (s3). Maybe we sat out some rounds? Or maybe the private folder only keeps some. Actually wait — maybe we played m15 or m16 too but the ls output was truncated before showing data/private/s3 fully. The private section showed only 4 decisions.jsonl files: s0/m2, s3/m11, s3/m3, s3/m7. So in s3 we played m3, m7, m11 — that's 3 matches in 16. With 8 clubs and 4 matches per round, 16 matches = 4 rounds, each club plays 4. Unless... some matches don't involve us? No wait, 8 clubs × 4 rounds = 32 club-slots / 2 = 16 matches. Every club plays every round. So we should have 4 matches in s3. But only 3 decisions.jsonl. Hmm, maybe one match's private data wasn't listed due to truncation? The private listing showed exactly 4 files and then moved to seasons/s0. It seems complete for that section.
Wait, maybe we sat out a round (sit_out)? The budget says "you have used $1.06 across 2 session(s)" and 15 rounds still to play. Season purse $7.00, 15 rounds left of... if the season has 18 rounds total and we're after round 3 (16 matches ≈ 4 rounds)... hmm, 15 rounds still to play. If s3 is the current season with 16 matches played = 4 rounds done, and 15 rounds remain, that's 19 rounds total? Odd number. Or maybe rounds include byes.
Actually, maybe the harness ran our committed code for round 4 matches without a session (that's the point of sit_out / last committed code plays). The budget line says "used $1.06 across 2 sessions" — sessions 1 and 2 (night 8 and night 9?). The notes mention "Session 2 (2026-09-03, post-m11)". So this is session 3 (night 10?). Hmm, but sessions listed are night_000, 003, 004, 008, 009. So tonight might be night_010 or similar.
Key question: has there been a match since m11 involving us? The notice says match 16 was Muse Spark FC v Real Machina, already rendered. Matches 17-20 are round 4 under the new buzzer rule. If m16 is in round 4, then rounds are 4 matches each: round 1 = m1-4, round 2 = m5-8, round 3 = m9-12, round 4 = m13-16? But the notice says "Match 17 is inside round 4" — so round 4 spans m13-20? That would be 8 matches in round 4. Hmm, maybe rounds aren't uniform. Or maybe there are more clubs. Whatever.
Actually wait — maybe s3's 16 matches include matches where we played via last-committed code without private decisions being saved? No, private decisions.jsonl is our own club's private log — it should exist for every match we play.
Let me just check the table and find our matches. Best move: read data/seasons/s3/table.json (7 KB in s0, probably similar). That gives the standings and maybe recent results. Then find our latest match digest.
Actually, more efficient: grep "frontier_glm" in data/seasons/s3 — the matching lines will include fixture.json contents and file paths, revealing which match dirs involve us. Let me do that. Or grep for "glm" in data/seasons/s3/table.json.
Hmm, but grep returns matching lines — fixture.json files would match. Let me do: {"tool": "grep", "pattern": "frontier_glm", "path": "data/seasons/s3"}. That could return a lot of lines (comms, match.json mentions). Maybe restrict to fixture files? Grep path may be a file only, not a glob. Let me instead read the table first: {"tool": "read", "path": "data/seasons/s3/table.json"}. That's one read, ~7 KB, gives standings and possibly results by round.
Also I should check: did we play m15 or m16? If the flash-lite switch hasn't been tested in a real match, then tonight's job is different: verify the buzzer-rule implications and maybe improve before round 4 matches 17-20. The notice says matches 17-20 run the new buzzer rule, and match 16 already aired. So our next match is m17, m18, m19, or m20 — under the NEW buzzer rule. That's the big thing to prepare for: last-second shots are unblockable; clear loose balls before the buzzer; second half is ~12 s longer.
So tonight's priorities:
1. Find our latest match (m11? or later) digest — check if flash-lite fixed deadlines. If no new match, m11 is still latest.
2. Check the table to see where we stand.
3. Adapt team.py for the buzzer rule: e.g., in the last ~5-8 s of a half, bias toward shooting/clearing; avoid holding the ball near our goal as the clock runs out.
4. Practice, lint, done.
Let me start by reading the s3 table. Also maybe check league.yaml for schedule. Let me read table.json first.
Actually, let me think about what ls showed: data/seasons/s3 wasn't fully shown due to truncation. The private decisions show our s3 matches: m3, m7, m11. If we'd played a 4th (say m15), there'd be a decisions.jsonl. There isn't. So either the season has had only 3 rounds of matches involving us... but 16 matches exist. 16 matches / 4 per round = 4 rounds. Hmm, unless some rounds have more matches (e.g., some clubs play twice?). Or the season has byes.
Wait — maybe I'm wrong that every club plays every round. "sit_out (1-3) — you will not be run for that many rounds and will pay nothing for them — your committed code plays on." So even sitting out, our code plays. So we play every round regardless. Unless... the "15 rounds still to play" and s3 having 16 matches... Let me count: if the season is 18 rounds and 3 are done (12 matches), but 16 matches exist... doesn't fit either.
Hmm, actually maybe matches m13-m16 are round 4 and were rendered already (m16 mentioned as rendered). The notice says "Match 17 is inside round 4, so round 4 is split" — so round 4 = m13-m20?? That's 8 matches. With 8 clubs, a round-robin round has 4 matches. 8 matches in round 4 would mean each club plays twice. Odd. OR the league has more than 8 clubs... "You compete against three other frontier-model gaffers and four frozen founding clubs" — 4 frontier + 4 founding = 8 clubs. 4 matches per round.
Unless rounds are double-rounds (home and away)? 8 clubs, double round-robin = 56 matches per season... s2 had 28 matches (exactly half of 56 — a single round-robin season?). s3 has 16 so far.
Whatever — the details will be in table.json / league.yaml. Let me read the table.
Plan for this turn: read data/seasons/s3/table.json. Short prose first.
Actually, I realize I should be careful with budget: $2.50 session cap, 28 turns, 1h30m. Spent $0.02. Fine.
Let me also think ahead: the key off-pitch job tonight is the buzzer rule. Changes to consider in team.py:
1. End-of-half behaviour: when time_remaining_s is low (say < 8 s) in a half:
- If we have the ball anywhere in the opposition half: shoot immediately (kick toward goal) rather than dribbling/holding.
- If the ball is loose near our goal: clear it hard upfield/away (not just cover).
- Avoid holding the ball (possession) near the buzzer — a held ball at the buzzer becomes a dead ball with no goal chance; a struck shot keeps rolling and can score.
2. The second half is ~12 s longer — nothing to change code-wise, but time_remaining_s semantics unchanged.
3. Do we know which half we're in? The observation presumably includes time_remaining_s and maybe half. Need to check team.py and the SDK to see what's available. If we can't tell half from time_remaining_s alone (match_time_s/2 per half), we can infer: if time_remaining_s > match_time_s/2 we're in the first half. Actually time_remaining_s is the match clock — presumably counts down from match_time_s (600?) to 0 across both halves? "Both halves are now exactly match_time_s/2 of football" and "your time_remaining_s is the match clock and its meaning is unchanged". If the clock stops at the buzzer and restarts at kickoff, then time_remaining_s at any moment tells you the half: first half runs from 600 to 300, second from 300 to 0 (if match_time_s=600). From the notes: "second halves ran 288 s against the first half's 300" — so match_time_s/2 = 300, match_time_s = 600. So half boundary at 300 s.
So in code: seconds_to_half_end = time_remaining_s - 300 if time_remaining_s > 300 else time_remaining_s. Wait: first half: time_remaining goes 600→300, so time until half end = time_remaining_s - 300. Second half: 300→0, time until match end = time_remaining_s. Good.
4. Buzzer-window logic: in the last ~6-10 s before half end:
- Presser: if within kicking range of ball and goal-ward, SHOOT (aim corners maybe). If ball near own goal, CLEAR (kick toward opposition half, wide).
- Cover: maybe step to ball if it's loose near our goal in final seconds? The shell currently has cover hold the ball→own-goal line. In the final seconds, a loose ball in our box is the danger the notice flags. Maybe in final 10 s, if ball is within ~4 m of our goal, both robots converge to clear it.
Let me first read team.py to see the current structure. I know it's 7 KB. Also check what the SDK offers (gauntlet.rfl_sdk / gauntlet.football agent factories) — reference/ has the sample implementation. But budget-wise, team.py + table.json + maybe m11 digest re-check... Actually m11 digest numbers are already in NOTES (missed 64/67, latency 2.34). The question is whether a NEWER match exists. Let me check the table and league.yaml.
Turn plan: read data/seasons/s3/table.json. Then decide.
Actually — to find whether we played after m11, the table.json likely lists per-club record and maybe recent results. Let me read it. One read, cheap.
Prose: brief — "The ls came back truncated before s3's match list; the private decisions show our s3 matches as m3, m7, m11 — so the flash-lite switch may not have been tested in anger yet. Reading the table to confirm where we stand and what's next."
The listing truncated before s3's matches, but the private decisions folder tells me something important: our only s3 matches with private logs are m3, m7 and m11 — so the flash-lite switch may not yet have been tested in a real match. Round 4 (matches 17–20) runs under the new buzzer rule, and that's what I need to prepare for. First, the table to confirm where we stand.
Readdata/seasons/s3/table.json
The league answered24,163 characters
[read data/seasons/s3/table.json] {
"played": [
{
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"home": "real_machina",
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5,
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],
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]
},
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},
{
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{
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],
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},
"dir": "runs/league/s3/m11_real_machina_frontier_glm"
},
{
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{
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...[showing 0-24000 of 30122 chars. Read on with {"tool": "read", "path": "data/seasons/s3/table.json", "offset": 24000}]
(0.0s)The league answered991 characters
model error (1/3): InternalServerError: Error code: 504 - {'type': 'https://developers.cloudflare.com/support/troubleshooting/http-status-codes/cloudflare-5xx-errors/error-504/', 'title': 'Error 504: Gateway time-out', 'status': 504, 'detail': 'The origin web server did not respond to Cloudflare within the allowed time. This typically means the origin is overloaded or a backend process is taking too long.', 'instance': 'a37720f68d00edfa', 'error_code': 504, 'error_name': 'origin_gateway_timeout', 'error_category': 'origin', 'ray_id': 'a37720f68d00edfa', 'timestamp': '2026-09-07T16:37:19Z', 'zone': 'api.aimlapi.com', 'cloudflare_error': True, 'retryable': True, 'retry_after': 120, 'owner_action_required': True, 'what_you_should_do': '**Wait and retry.** Back off for at least 120 seconds. If the error persists, the website operator should investigate long-running processes on the origin server.', 'footer': 'This error was generated by Cloudflare on behalf of the website owner.'}The league answered16 characters
backing off 120s
Thought for 2,441 words
Let me think about where I am. The session log shows:
1. I tried to ls data/seasons/s3 but got a huge listing that truncated before showing s3's matches. However, I learned from the private decisions folder that our s3 matches with private logs are m3, m7, m11.
2. I read the s3 table.json which showed fixtures 1-3 (and truncated at fixture 4). I saw m3: synthetic_athletic 4 - 3 frontier_glm (we lost 4-3 away at Synthetic Athletic).
3. Then a 504 error and backoff.
Budget: $0.04 of $2.50 spent, 1h14m of 1h30m left, 24 of 28 turns left.
Key facts from the table so far:
- m3: synthetic_athletic 4-3 frontier_glm — we lost 4-3. That was presumably before the flash-lite switch (the switch was made 2026-09-03 after m11).
- Wait, the notes say m11 was Real Machina 10-2 (we lost 10-2 at Real Machina). And m7 was 16-3 at Singularity United. So s3 has 16 matches, and we've played m3, m7, m11 (those have private decisions logs). The flash-lite switch was made after m11, so it hasn't been tested in a real match yet — unless there are matches after m11 in s3 (m12-m16). The private decisions folder only has m3, m7, m11 for s3, which suggests those are the only matches we've played in s3 so far... but wait, s3 has 16 matches. Hmm, but the table.json read was truncated at fixture 4. The season is "in round 4" per the notices — match 16 was already rendered, matches 17-20 run the new buzzer rule. So s3 has 16 matches played, and round 4 (matches 17-20) is upcoming.
Wait, but the private decisions only show m3, m7, m11 for s3. If 16 matches have been played in s3, we should have played more than 3. Unless... each round has 4 matches (8 clubs), so 16 matches = 4 rounds, each club plays once per round = 4 matches per club. But we only have 3 private decision logs (m3, m7, m11). Hmm, m3 is round 1, m7 is round 2, m11 is round 3. So round 4 (matches 17-20) hasn't been played yet — but the notice says match 16 was already rendered and matches 17-20 run the new rule. Wait, that contradicts: if s3 has 16 matches and match 16 was rendered, then round 4 = matches 13-16? Let me re-read.
"Match 17 is inside round 4, so round 4 is split... Match 16 (Muse Spark FC v Real Machina) was already rendered when this landed... Matches 17 to 20 run the new one."
So matches 17-20 are in round 4 and haven't been rendered yet. That means s3's 16 matches are rounds 1-3 plus part of round 4? If each round is 4 matches (8 clubs, 4 fixtures per round), then 16 matches = 4 rounds. But matches 17-20 are round 4... so 16 matches = rounds 1-3 would be 12 matches. Hmm, 16 matches with matches 17-20 in round 4 means rounds 1-3 had 16 matches? That's 5.33 per round. Maybe rounds aren't uniform.
Actually wait — maybe s3 has 20 matches total and only 16 have been played so far ("data/seasons/ holds s3 (16 matches)" — the 16 matches exist in the archive). Matches 17-20 are the upcoming round 4. So rounds 1-3 = 16 matches? That's odd but possible if some rounds had more matches. Or maybe rounds are: round 1 = matches 1-6, round 2 = 7-11, round 3 = 12-16, round 4 = 17-20. Something like that.
Our private decisions in s3: m3, m7, m11. If we play once per round, we'd have played in rounds 1, 2, 3 — m3 (round 1), m7 (round 2), m11 (round 3). And match 16 was Muse Spark v Real Machina — not us. So our next match is in matches 17-20 (round 4), under the new buzzer rule. The flash-lite switch has NOT yet been tested in a real match — the notes said "switched 2026-09-03 after m11", and m11 was our most recent match.
So tonight's priorities:
1. Check the table to see where we stand (I got fixtures 1-3, need the rest — but maybe I can be more efficient with grep or reading specific parts).
2. Read m11's digest? No wait — the notes from night 9 already dissected m11. The still-open item was m7's 16-3 at Singularity United — read its digest to learn whether it was the same latency problem or tactical.
3. Prepare for the buzzer rule: the key change is "play the clock" — a shot struck in the last second of a half is worth taking; a ball loose in front of your own goal as the clock runs out is a danger — clear it before the buzzer. Also "whether your players hold the ball when the clock is nearly out" — review that.
So the concrete code change for tonight: add clock-awareness to the behaviour. When time_remaining_s is low (say < 10s of a half), the presser should shoot at goal from anywhere plausible rather than dribbling/holding, and defenders should clear the ball away from own goal rather than holding it. Also, after the buzzer nothing can move, so no code changes needed for that — but the shell should know that a shot in the last second is unblockable.
Let me plan the session efficiently given 24 turns and ~$2.46 left:
1. Read m7's digest (the still-open item) — 1 turn.
2. Read m11's digest to confirm the latency numbers (already in notes, maybe skip — notes have it: 64/136 and 67/136 missed, 2.34s mean). Skip.
3. Read current team.py to see the code — 1 turn (7 KB, fits in one read).
4. Make the buzzer-aware change — 1-2 turns (write or replace).
5. Lint — 1 turn.
6. Practice — 1 turn (maybe 2).
7. Note in NOTES.md — 1 turn.
8. Done — 1 turn.
That's about 8-10 turns, well within budget. Maybe also check the table's remaining fixtures to see who we play next — grep for frontier_glm in table.json to find our fixtures. That's cheap.
Also the 504 error — the harness backed off 120s. That's the aggregator being flaky. Not something to report necessarily; it's transient. Actually, the notices mention the aggregator doesn't honour cache markers and AFC Fable routes direct to Anthropic. A 504 from the aggregator is a real issue that cost me clock time (2 minutes of my 1h30m). But it's retryable and the harness handled it. I could report it — reporting is free. It might be worth noting that the aggregator 504'd during a session, costing clock. But is it a league problem? The league chose the aggregator. It's evidence for the league that the aggregator is unreliable. I'll consider it — maybe a quick report at the end if budget allows. Actually, the notice already acknowledges aggregator issues (cache marker). A 504 mid-session that eats 2 minutes of clock is a different failure. I think it's worth a brief report — it's free and specific. But let me focus on football first.
Let me also think about what the buzzer rule means for the code:
- Each half is match_time_s/2. From the goals data, matches run to ~600s total (goals at t up to 585). So match_time_s = 600, each half 300s. The clock: time_remaining_s is the match clock. First half ends at 300s remaining (i.e., 300s elapsed), second half at 0.
- Key behaviours to add:
a) **Last-second shot**: if we have the ball (or are near it) and time_remaining_s is within ~8s of a half end (time_remaining_s <= 8 for second half, or time_remaining_s in [292, 300] for first half — wait, need to know how time_remaining_s works. If match_time_s = 600 and we're in the first half, time_remaining_s counts down from 600? Or from 300? Hmm. "your time_remaining_s is the match clock and its meaning is unchanged". The match clock probably counts the whole match: 600 down to 0, with the half at 300. So first half: time_remaining_s in (300, 600]; second half: time_remaining_s in (0, 300]. Half ends when time_remaining_s hits 300 (first) or 0 (second).
Actually I need to check what the observation gives. Let me look at team.py and maybe the SDK reference. The shell code will show how time is used, if at all.
b) **Defensive clear**: if the ball is loose in our defensive third and the clock is nearly out, kick it away (toward the opposition half / touchline) rather than trying to control it.
c) **Don't hold the ball near the end**: if we're leading and the clock is nearly out, clear it far away rather than dribbling near our own goal. If trailing, shoot from anywhere.
- Also, after the buzzer, no decisions are taken — so nothing to code there.
- The shot in the last second is unblockable — so the presser should take a shot from anywhere within, say, 6-8m of goal in the last ~5s rather than trying to walk it in.
Let me now read team.py to see the current structure. Also I should check how time_remaining_s appears in observations. Let me grep for "time" in team.py and reference.
Plan for this turn: read club/team.py (7 KB, one read). Actually, let me first say a brief paragraph about what I'm doing, then the JSON.
Actually, I realize I should be careful about the truncated table read — I don't know our full record. Let me grep the table for our fixtures: grep "frontier_glm" in data/seasons/s3/table.json would give lines, but the table is JSON with fixtures as objects; grep would give the "home"/"away" lines and score lines separately, which is hard to pair. Better: read the table with offset to get the rest. The table is 7 KB... wait, the ls said data/seasons/s3/table.json — actually I didn't see its size. The s0 table was 7 KB. The s3 table with 16 matches is probably ~30 KB. My read got truncated at fixture 4. Hmm, actually the read returned fixtures 1-3 fully and truncated at fixture 4. The read serves 24 KB at a time. So the table is bigger than 24 KB. I could read with offset ~24000 to get the rest, but that's 1-2 more turns.
Alternative: grep for "frontier_glm" with context... grep returns matching lines only. In pretty-printed JSON, "away": "frontier_glm" would be one line, and the score is several lines above. Not ideal but the digest of each of our matches is better. Actually, what I really need:
1. Our record in s3 (W/D/L, goals for/against) — from the table or from our match digests.
2. m7's digest (the open item).
3. Who we play next (round 4, matches 17-20) — the fixture list might be in league.yaml or the table's "upcoming" section.
Let me be efficient. This turn: read m7's digest (the open item from notes). Then team.py. Then decide the change.
Actually wait — the notes say m7 was "16–3 at Singularity United". Let me confirm from the digest and get the per-player numbers to determine if it was latency (like m11) or tactical. The m11 fix (presser-only calls + flash-lite) may have already fixed m7's problem if it was latency. If m7 was tactical (e.g., we got overrun defensively), that's a different fix.
Let me do: read data/seasons/s3/m7_singularity_united_frontier_glm/digest.json. Digests are small (3-4 KB), one read each.
Then read club/team.py.
Then make the buzzer change.
Let me also think about what the change looks like in code. I haven't seen team.py yet in this session, so I'll read it first. From the notes, the structure is: decide() with role assignment (presser/cover), LLM call for presser only, shell fallbacks (press/kick at goal inside 1.2m; cover otherwise), ball memory 3s, wall avoidance 0.75m.
The buzzer change would add, in the shell (not the LLM — the LLM might not reason about the clock reliably, and the shell must be deterministic):
- Compute seconds_to_buzzer: if time_remaining_s > half_time (300), first half: t_buzz = time_remaining_s - 300; else t_buzz = time_remaining_s.
- If t_buzz <= ~6s:
- If we (either robot) can reach the ball before the buzzer and we're in the opposition half: kick at goal immediately (from any distance — unblockable after buzzer, but before buzzer it can be blocked; still, a shot is better than holding).
- If the ball is in our defensive third: kick it clear — toward the opposition half, wide if needed — never toward our own goal, never hold.
- Also maybe: in the last ~15s, if leading, the cover robot positions between ball and own goal even more conservatively.
But I need to see how the code gets time. The observation probably includes time_remaining_s. Let me check team.py and the SDK.
One more consideration: the practice match — does practice run under the new buzzer rule? Practice plays a real match with current code vs mirror. The notice says "From match 17 onwards" — practice might or might not have the buzzer. Either way, practice verifies no crash.
Also worth checking: does the engine's match_time_s = 600? From goals at t=585.4 and 584.0, yes, ~600s total, 300s halves. The notice says "second halves ran 288 s against the first half's 300" before — so match_time_s/2 = 300.
Let me also consider: should I check the models registry for any new models? The playbook says re-check each window. The registry is 2 KB, cheap to read. Maybe worth a quick look — if a faster/cheaper model appeared, consider it. But flash-lite at 1.50s measured was already good; and the switch was just made. The playbook says "trust only measured match numbers" — flash-lite hasn't had a real match yet. So no switch tonight; wait for the next match's digest. Skip the registry read to save turns. Actually, it's 2 KB and one turn... I have 24 turns. Let me prioritize: m7 digest, team.py, change, lint, practice, note, done. That's ~8 turns. I have room for the registry and maybe the rest of the table. But every read costs tokens too. Let me keep it tight but not starved.
Priority order:
1. m7 digest (open item, informs whether tactical fix needed beyond buzzer).
2. team.py (must read before editing).
3. Maybe grep reference/SDK for time_remaining_s to confirm the field name.
4. Edit.
5. Lint.
6. Practice.
7. Note.
8. Done.
Let me start with m7's digest. Brief prose first.
Actually, one thing about the 504: the harness said "backing off 120s" and the clock shows 1h14m left of 1h30m — so ~14 min elapsed including the backoff. Fine.
Let me write the turn: brief prose + read m7 digest.
The 504 cost me two minutes of clock but nothing else — back on it. From the table so far: we lost 4–3 at Synthetic Athletic (m3), and the notes say m7 was a 16–3 hiding at Singularity United that I never dissected. That's the open item, and it matters tonight because if m7 was the same latency disease as m11, the flash-lite fix already covers it and I can spend this session on the buzzer rule; if it was tactical, I have two problems. Reading m7's digest now.
Readdata/seasons/s3/m7_singularity_united_frontier_glm/digest.json
The league answered3,848 characters
[read data/seasons/s3/m7_singularity_united_frontier_glm/digest.json] {
"_what": "League-computed summary of this match. The raw event tape is in match.json; this is the same data counted up so it fits in a read. Facts only \u2014 no advice.",
"score": [
16,
3
],
"winner": "A",
"teams": {
"A": {
"name": "Singularity United",
"code": "SGU",
"players": [
"Haalandroid",
"BellingRAM"
]
},
"B": {
"name": "GLM FC",
"code": "GLM",
"players": [
"Zhi",
"Pu"
]
}
},
"match_time_s": 600.0,
"half_breaks": [
300.0
],
"honest_latency": true,
"goals": [
{
"t": 44.5,
"team": "A",
"scorer": 0,
"replay_s": 5.0
},
{
"t": 55.6,
"team": "A",
"scorer": 0,
"replay_s": 5.0
},
{
"t": 69.8,
"team": "A",
"scorer": 0,
"replay_s": 5.0
},
{
"t": 82.1,
"team": "A",
"scorer": 1,
"replay_s": 5.0
},
{
"t": 103.1,
"team": "B",
"scorer": 3,
"replay_s": 5.0
},
{
"t": 121.6,
"team": "A",
"scorer": 1,
"replay_s": 5.0
},
{
"t": 137.2,
"team": "A",
"scorer": 0,
"replay_s": 5.0
},
{
"t": 153.0,
"team": "A",
"scorer": 3,
"replay_s": 5.0
},
{
"t": 167.0,
"team": "A",
"scorer": 0,
"replay_s": 5.0
},
{
"t": 226.1,
"team": "A",
"scorer": 1,
"replay_s": 5.0
},
{
"t": 239.3,
"team": "A",
"scorer": 1,
"replay_s": 5.0
},
{
"t": 285.6,
"team": "B",
"scorer": 1,
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},
{
"t": 324.7,
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"scorer": 1,
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},
{
"t": 424.1,
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},
{
"t": 466.2,
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},
{
"t": 482.4,
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},
{
"t": 512.2,
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"replay_s": 5.0
},
{
"t": 529.7,
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},
{
"t": 588.9,
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}
],
"events_total": 405,
"event_counts": {
"touch": 178,
"through": 30,
"kick": 166,
"near_miss": 5,
"wall": 22,
"fall": 4
},
"event_counts_by_half": {
"half_1": {
"touch": 80,
"through": 18,
"kick": 74,
"near_miss": 3,
"wall": 9,
"fall": 2
},
"half_2": {
"touch": 98,
"kick": 92,
"fall": 2,
"through": 12,
"wall": 13,
"near_miss": 2
}
},
"falls": {
"total": 4,
"by_opponent": 1,
"unforced": 3,
"by_half": {
"half_1": 2,
"half_2": 2
},
"times_s": [
173.6,
272.9,
317.2,
393.5
]
},
"players": [
{
"index": 0,
"team": "A",
"agent": "llm:google:gemini-flash-lite-latest",
"falls": 3,
"recoveries": 3,
"touches": 55,
"decisions": 217,
"invalid_actions": 0,
"missed_deadlines": 25,
"abandoned": 0,
"mean_decision_latency_s": 1.909
},
{
"index": 1,
"team": "A",
"agent": "llm:google:gemini-flash-lite-latest",
"falls": 1,
"recoveries": 1,
"touches": 62,
"decisions": 220,
"invalid_actions": 0,
"missed_deadlines": 27,
"abandoned": 0,
"mean_decision_latency_s": 1.891
},
{
"index": 2,
"team": "B",
"agent": "<rfl_team_frontier_glm.GLMPlayer object at 0x118dc1e50>",
"falls": 0,
"recoveries": 0,
"touches": 30,
"decisions": 64,
"invalid_actions": 0,
"missed_deadlines": 99,
"abandoned": 2,
"mean_decision_latency_s": 2.551
},
{
"index": 3,
"team": "B",
"agent": "<rfl_team_frontier_glm.GLMPlayer object at 0x11961ac00>",
"falls": 0,
"recoveries": 0,
"touches": 31,
"decisions": 69,
"invalid_actions": 0,
"missed_deadlines": 107,
"abandoned": 1,
"mean_decision_latency_s": 2.482
}
],
"dropped_balls": [],
"tokens_in": 2778501,
"tokens_out": 74634,
"est_cost_usd": 0.4288
}
(0.0s)Thought for 1,017 words
Let me digest what I just learned from m7's digest:
- m7: Singularity United 16 - 3 GLM FC
- Our players (Zhi, Pu): decisions 64 and 69, missed deadlines 99 and 107 (!), mean latency 2.55/2.48s
- Their players (Haalandroid, BellingRAM on gemini-flash-lite): decisions 217 and 220, missed deadlines 25 and 27, mean latency 1.91/1.89s
So m7 was the SAME latency disease as m11: we were out-decided 437 to 133, missed ~206 of ~206 deadlines... wait, missed_deadlines 99 and 107 out of what total? Decisions 64 and 69 — so missed deadlines exceed decisions, meaning missed deadlines are counted against total ticks (~136 per half? or ~200+ total). Anyway: we made 64-69 decisions while they made 217-220. We were massively out-decided. Mean latency 2.5s vs 1.9s.
Interesting: their flash-lite measured 1.89-1.91s in m7, and 1.50s in m11. Our luna measured 2.34s in m11 and 2.48-2.55s in m7.
So m7 was the same disease: slow model + calling for both robots every tick. The flash-lite switch + presser-only calls should fix both. Good — the open question from NOTES is answered: m7 was latency, not tactics. Though 16-3 also suggests tactical gaps, the primary cause was being out-decided 437-133.
Also notable: our touches were 30-31 vs their 55-62. And we had 0 falls vs their 4 — we don't fall, we just don't get to the ball.
Now, the current session priorities:
1. The buzzer rule (matches 17-20, round 4). Key implications:
- A shot in the last second of a half is unblockable — worth taking.
- A loose ball in front of our own goal as the clock runs out is a danger — clear it before the buzzer.
- Second half is ~12s longer.
- The notice says: "the one thing worth reviewing is whether your players hold the ball when the clock is nearly out."
So the change for tonight: add clock-awareness to the behaviour layer. When time_remaining_s is low (say < 10s in a half), the presser should shoot at goal rather than dribble/hold, and defenders should clear the ball away from own goal (boot it upfield/wide) rather than trying to control it.
Let me look at team.py to see the current structure. I have 23 turns left, $2.43 of session budget, ~1h11m. Let me be efficient.
Plan:
1. Read club/team.py (7 KB, one read).
2. Make the buzzer-awareness change:
- If time_remaining_s < ~8s (end of half — need to know how to detect half; time_remaining_s is the match clock; half ends at 300s elapsed, i.e., time_remaining 300 at start... actually match_time_s 600, half_breaks [300]. time_remaining_s counts down from 600? Or per half? The notice says "Both halves are now exactly match_time_s / 2 of football" and "your time_remaining_s is the match clock and its meaning is unchanged". So time_remaining_s presumably counts down from 600 to 0, with the half break at 300 remaining. So end of first half when time_remaining_s approaches 300 from above; end of second half when it approaches 0.
- So "clock nearly out" = time_remaining_s < ~8 (end of match) OR 300 < time_remaining_s < ~308 (end of first half).
- In that window: if we have the ball or are near it, KICK AT GOAL (a shot struck in the last second is unblockable). If the ball is loose near our own goal, clear it hard upfield/wide.
3. Practice once or twice, lint, note, done.
Also should I check what the shell's kick fallback does — "press / kick at goal inside 1.2 m; cover otherwise". The LLM decides otherwise. For the buzzer window, I want to override the LLM entirely (no model call — instant shell decision) with: if within kicking range of ball, kick toward opponent goal (hard); if ball is in our defensive third, clear it wide/upfield.
Actually wait — after the buzzer, nothing can touch the ball. Before the buzzer (last few seconds), everything still works normally. So the play is: in the last ~8 seconds, take any shooting chance (shoot early rather than dribbling closer), and clear danger balls from our box.
One nuance: the ball keeps rolling after the buzzer for 5-10s until it comes to rest. A goal counts if it crosses in that window. So a shot struck at t=299.5 that takes 2s to cross still counts. Also a ball rolling toward our goal at the buzzer is a threat for up to 10s. So clearing wide is important — a clearance up the middle could... no wait, after the buzzer nothing can touch it, so a clearance that rolls toward our own goal would be bad. Clear WIDE or upfield away from goal.
Also: "the corner push-panels disarm" — irrelevant to behaviour code probably.
Let me also think about whether the LLM even knows the clock. The observation presumably includes time_remaining_s. The shell can read it too. I'll implement in the shell: a `buzzer_window` flag; when active, skip the LLM call and act directly. That also saves latency in the closing seconds, which is exactly when latency hurts most.
Let me read team.py now.
Also, budget: $2.43 left in session, 23 turns. Practice costs ~$0.05-0.10 each. Fine.
One more consideration: should I also address the "cover robot is passive" gap? The playbook says one change per session where possible. The buzzer change is the priority because round 4 starts with match 17 under the new rule — possibly our next match. Keep it focused: buzzer awareness. Maybe also a tiny tweak: in the final seconds, BOTH robots should chase the ball if it's in shooting range? Hmm, careful — if both chase, we lose shape. But at the buzzer, shape doesn't matter after power cuts. In the last ~5s, if the ball is in the opponent's half within our shooting range, both robots going for the shot is fine. But keep it simple: presser shoots, cover... if the ball is near our own goal, cover should clear it too. Actually the cover is goal-side, so a loose ball in our box might be nearer the cover. Let me see the code first.
Let me read team.py.
m7's digest answers the open question from my notes: it was the same latency disease as m11, only worse. We were out-decided 437–133 (their flash-lite: 217/220 decisions at ~1.9 s; our luna: 64/69 decisions at ~2.5 s, missing 99 and 107 deadlines). Zero tactical dissection needed — the flash-lite switch plus presser-only calls already treats it. So tonight's session goes to the buzzer rule: with round 4 starting at match 17, my players need clock-awareness in the closing seconds of each half. Reading the current behaviour code.
Readclub/team.py
The league answered7,015 characters
[read club/team.py] """GLM FC — behaviour layer. Founded Founding Night by GLM-5.3 for Zhipu.
Each player runs the league's LLM football agent (fast tier) for its read
of the game, wrapped in a deterministic tactical shell that enforces the
one structural rule of 2v2 football: exactly one robot presses the ball,
the other covers the line between ball and own goal. The shell also
validates every reply, so a malformed or missing model answer degrades to
sound positional football rather than an error.
Imports: stdlib math and gauntlet.football only.
"""
import math
X_LIMIT = 6.5 # pitch is 14 x 9 m; stay off the walls
Y_LIMIT = 4.0
COVER_OFFSET_M = 2.0 # cover stands this far goal-side of the ball
SWITCH_MARGIN_M = 1.5 # hysteresis: presser changes only if clearly beaten
BALL_MEMORY_S = 3.0 # trust the world model's ball memory this long
KICK_RANGE_M = 1.2 # inside this, strike at goal rather than dribble
def _clamp(pt):
return [max(-X_LIMIT, min(X_LIMIT, pt[0])),
max(-Y_LIMIT, min(Y_LIMIT, pt[1]))]
def _dist(a, b):
return math.hypot(a[0] - b[0], a[1] - b[1])
class GLMPlayer:
"""An LLM brain inside a positional shell."""
def __init__(self, agent, shirt, shared):
self.agent = agent
self.shirt = shirt
self.shared = shared # role state shared with the teammate
self.last_ball = None # [x, y] last credible ball position
# -- engine contract ------------------------------------------------
def begin_episode(self, log_dir=None):
self.shared["presser"] = None
self.last_ball = None
try:
self.agent.begin_episode(log_dir)
except Exception:
pass
def decide(self, obs):
# Fallen robots hold immediately: no model call, no latency.
self_state = obs.get("self") or {}
if self_state.get("fallen"):
return {"skill": "hold"}
you = obs.get("you") or {}
own_goal = you.get("defend_goal_xy") or [0.0, 0.0]
atk_goal = you.get("attack_goal_xy") or [0.0, 0.0]
me = self_state.get("field_xy") or [0.0, 0.0]
ball = self._ball(obs)
mate = self._teammate(obs)
presser, took_over = self._assign(ball, me, mate)
say = None
if ball is not None and presser == self.shirt:
# Only the presser spends a model call: it is the only role
# whose reply the shell can use. m11 cost us half our
# decisions to latency while the cover robot's calls were
# being discarded here anyway.
reply = {}
try:
r = self.agent.decide(obs)
if isinstance(r, dict):
reply = r
except Exception:
reply = {}
say = reply.get("say")
out = self._valid(reply)
if out is None:
if _dist(me, ball) <= KICK_RANGE_M:
out = {"skill": "kick_toward", "target": _clamp(atk_goal)}
else:
out = {"skill": "go_to_ball"}
if took_over and not say:
say = "Mine!"
else:
# Covering (or the ball is lost): hold the ball-goal line.
if ball is not None:
gx = own_goal[0] - ball[0]
gy = own_goal[1] - ball[1]
n = math.hypot(gx, gy) or 1.0
target = _clamp([ball[0] + gx / n * COVER_OFFSET_M,
ball[1] + gy / n * COVER_OFFSET_M])
else:
target = _clamp([(own_goal[0] + me[0]) / 2.0,
(own_goal[1] + me[1]) / 2.0])
out = {"skill": "walk_to", "target": target}
if say:
out["say"] = str(say)[:120]
return out
# -- internals ------------------------------------------------------
def _ball(self, obs):
ball = (obs.get("detections") or {}).get("ball")
if isinstance(ball, dict):
xy = ball.get("field_xy")
if xy and ball.get("age_s", 0.0) <= BALL_MEMORY_S:
self.last_ball = [float(xy[0]), float(xy[1])]
return self.last_ball
def _teammate(self, obs):
for t in (obs.get("detections") or {}).get("teammates") or []:
if isinstance(t, dict) and t.get("field_xy"):
xy = t["field_xy"]
return [float(xy[0]), float(xy[1])]
return None
def _assign(self, ball, me, mate):
"""One presser, with hysteresis; shared with the teammate."""
shirts = self.shared.get("shirts") or {self.shirt}
other = None
for s in shirts:
if s != self.shirt:
other = s
prev = self.shared.get("presser")
if prev not in shirts:
prev = None
if ball is None or (prev is not None and mate is None):
# Lost the ball or lost sight of the mate: keep the current role.
presser = prev if prev is not None else self.shirt
self.shared["presser"] = presser
return presser, False
my_d = _dist(me, ball)
mate_d = _dist(mate, ball) if mate else 99.0
if prev is None:
presser = self.shirt if my_d <= mate_d else other
elif prev == self.shirt:
presser = other if mate_d + SWITCH_MARGIN_M < my_d else self.shirt
else:
presser = self.shirt if my_d + SWITCH_MARGIN_M < mate_d else other
if presser is None:
presser = self.shirt
self.shared["presser"] = presser
return presser, (presser == self.shirt and prev != self.shirt)
@staticmethod
def _valid(reply):
"""Pass through only well-formed skill replies."""
skill = reply.get("skill")
if skill in ("go_to_ball", "hold"):
return {"skill": skill}
if skill in ("kick_toward", "walk_to", "turn_to"):
t = reply.get("target")
if isinstance(t, (list, tuple)) and len(t) == 2:
try:
x, y = float(t[0]), float(t[1])
except (TypeError, ValueError):
return None
return {"skill": skill, "target": _clamp([x, y])}
return None
def build_team(ctx):
from gauntlet.football import make_football_agent
cfg = ctx["config"]
base = ctx["team_index"] * 2
roster = cfg.get("players") or [{}, {}]
model = cfg.get("player_model") or "llm:mock:ok"
shared = {"presser": None, "shirts": set()}
players = []
for k in range(2):
agent = make_football_agent(
roster[k].get("model", model),
base + k,
seed=base + k,
prompt=roster[k].get("prompt", cfg.get("prompt", "football_v2")),
)
players.append(GLMPlayer(agent, base + k, shared))
shared["shirts"] = {p.shirt for p in players}
return {"players": players, "manager": None}
(0.0s)The league answered991 characters
model error (1/3): InternalServerError: Error code: 504 - {'type': 'https://developers.cloudflare.com/support/troubleshooting/http-status-codes/cloudflare-5xx-errors/error-504/', 'title': 'Error 504: Gateway time-out', 'status': 504, 'detail': 'The origin web server did not respond to Cloudflare within the allowed time. This typically means the origin is overloaded or a backend process is taking too long.', 'instance': 'a3773580883bc6b6', 'error_code': 504, 'error_name': 'origin_gateway_timeout', 'error_category': 'origin', 'ray_id': 'a3773580883bc6b6', 'timestamp': '2026-09-07T16:51:20Z', 'zone': 'api.aimlapi.com', 'cloudflare_error': True, 'retryable': True, 'retry_after': 120, 'owner_action_required': True, 'what_you_should_do': '**Wait and retry.** Back off for at least 120 seconds. If the error persists, the website operator should investigate long-running processes on the origin server.', 'footer': 'This error was generated by Cloudflare on behalf of the website owner.'}The league answered16 characters
backing off 120s
Thought for 1,610 words
Let me think about where I am. I've read m7's digest — confirmed it was the latency disease (our luna missed 99/107 deadlines, out-decided 437-133). The flash-lite switch plus presser-only calls already treats it. I've read most of team.py (it got truncated near the end — the `_valid` staticmethod and presumably the build_team function at the bottom).
Tonight's job: prepare for the buzzer rule (matches 17-20, round 4). The key tactical implications from the notice:
1. A shot struck in the last second of a half is worth taking — nothing can block it. So when time_remaining_s is low (end of half), the presser should shoot at goal from further out / immediately rather than dribbling.
2. A ball loose in front of your own goal as the clock runs out is a danger — clear it before the buzzer.
3. The clock stops at the buzzer; second half is now ~12s longer (300s each half instead of 288s).
4. Going down at the buzzer is not a fall.
What do I need to know about the observation? Does obs contain time_remaining_s? The notice says "your `time_remaining_s` is the match clock and its meaning is unchanged". So obs presumably has a time field. Let me check what field name — I should grep the reference implementation or the SDK for time_remaining_s to see where it lives in obs.
Also I need to see the rest of team.py (the truncated part) — the `_valid` method and `build_team`. Let me read the tail of team.py.
Plan for the code change (keep it small, one change per session):
Add clock-awareness to the shell:
- Read time remaining (and half info) from obs.
- When time_remaining_s is low (say <= 8s of the half — but how do I know which half? half_breaks at 300s; match_time_s 600. If time_remaining_s > 300 we're in the first half; the end-of-half threshold applies when time_remaining_s <= threshold OR time_remaining_s is within threshold of 300 (i.e., between 292 and 300 for first half end). Actually time_remaining_s counts down from 600. First half ends at 300 remaining. Second half ends at 0. So "near end of a half" = time_remaining_s <= T or (300 - T) <= time_remaining_s <= 300... wait: first half ends when 300s remain. So near end of first half: time_remaining_s in [300, 300+T]. Near end of second half: time_remaining_s in [0, T].
Hmm, but careful: at kickoff time_remaining_s ≈ 600, and it decreases. First half: 600→300. Second half: 300→0. So end-of-half windows: [300, 300+T] and [0, T].
In those windows:
- Presser: if within kicking range of ball, kick at goal immediately (no model call needed? or still call model but override to shoot?). The notice says a shot in the last second is worth taking because nothing can block it. But also, before the buzzer, play is normal. The value is: don't dribble when the buzzer is imminent — shoot first time. Also shoot from distance? A kick from far out will take time to travel; the buzzer window is 5-10s of physics. A ball struck at, say, t=299 that reaches the goal at t=305 still counts. So in the last ~10s, shooting from anywhere reasonable is good.
- Also: clear danger — if the ball is loose near our own goal in the last seconds, the presser should hoof it away/upfield rather than try to control.
Simplest robust change: in the end-of-half window, the shell takes over from the model entirely (no LLM call — also saves latency when it matters most):
- If I'm the presser and ball within KICK_RANGE: kick toward the opponent goal (or better: clear away from own goal if ball is in our defensive third).
- If presser but ball far: go_to_ball fast.
- Cover: normal cover shape (still fine), or maybe step to the ball if it's loose near our goal? Keep it simple: cover stays cover.
Actually, one more consideration: "A ball loose in front of your own goal as the clock runs out is a danger" — the presser is the one who goes to the ball by definition, so presser handles it. The cover holding the ball→goal line is still decent.
Also the notice says: "The one thing worth reviewing is whether your players hold the ball when the clock is nearly out." Our shell: presser inside KICK_RANGE kicks at goal; outside it goes to ball. The model might reply "hold" or dribble. In the final window we override with shell logic: always kick toward goal if in range; if not in range, go_to_ball.
What about kicking from beyond KICK_RANGE in the final seconds? If time is nearly out and I'm 3m from the ball, I can't reach it anyway. If I'm the presser near the ball but outside 1.2m... go_to_ball is right until in range.
But there's a subtlety: kick_toward from distance — is "kick_toward" only valid when close? The engine presumably executes a kick skill when the ball is kickable. The shell already uses kick_toward when within KICK_RANGE_M. Keep that.
Another subtlety: in the final window, should the presser shoot from further out — i.e., increase KICK_RANGE in the final window? If the ball is 2m away and there are 3s left, walking to it means the buzzer comes first. But you can't kick a ball you can't reach. The kick skill presumably requires proximity. So no.
What about the clear-the-lines case: ball near our goal, final seconds, presser in range → kick toward opponent goal is already a clearance upfield. Good — kicking at the opponent goal from our own third is a long clearance. Fine.
One more: after the buzzer, no decisions are taken — so nothing to handle there. The engine just stops calling us, presumably. Or maybe it calls and ignores? "No decisions are taken" — so we don't need to handle it.
Also worth considering: the second half is now 12s longer — nothing to change, time_remaining_s meaning unchanged.
Do I know the obs field name for time? The notice says `time_remaining_s`. I should verify how it appears in obs — maybe obs["time_remaining_s"] or obs["clock"]["time_remaining_s"]. Let me grep the reference implementation and the SDK. reference/ is the public sample-team implementation. Let me grep for time_remaining in reference/ and in data (maybe in match.json or the rules). Also check RFL_RULES.md for the observation schema.
Let me also read the tail of team.py (truncated at the `_valid` method). I need the full file before editing. The read tool serves 24KB at a time; team.py is 7KB so the truncation was in the harness display, not the read. Actually the output said "[truncated]" — the harness truncated the display. I got most of it; the missing part is the end of `_valid` and `build_team`. Let me read with offset to get the tail, or grep for "def build_team" with context. Simpler: read the file with an offset near the end. The file is 7KB; offset 5000 or so would give the tail. Or grep "def " to see structure. Let me just read offset ~4500.
Actually, let me be efficient with turns. I have 21 turns left, $2.41 of session budget, ~1h clock. Two 504s already cost 4 minutes of clock.
Turn plan:
1. Grep for time_remaining in reference/ and data/RFL_RULES.md to confirm the obs field name. (one grep call, path can be a root? "path may be a file or one of club/, data/, reference/" — so I can grep reference/ root.)
2. Read tail of team.py (offset).
3. Write the change to team.py.
4. Lint.
5. Practice (90s).
6. Maybe adjust + practice #2.
7. Update NOTES.md + PLAYBOOK.md (buzzer section).
8. Done.
That's ~8-9 turns. Comfortable.
Let me do step 1 and 2 in one turn? No — exactly one JSON object per turn. OK, sequence them.
Actually, can I combine grep patterns? One grep per turn. Grep "time_remaining" in reference/ first — that's the sample implementation, most likely to show obs usage. Also RFL_RULES.md likely documents the observation schema. Let me grep data/RFL_RULES.md for time_remaining too. I'll do reference/ first since that shows actual code usage.
Hmm, but which is more likely to have it? The rules doc documents the reply contract and observations. The notice says "your `time_remaining_s` is the match clock" — implying it's a known obs field. Let me grep both roots in two turns, or grep "time_remaining" with path "reference/" then if nothing, try rules. Actually I could grep the whole data/ root but that's huge (decisions.jsonl 1MB+ each...). grep returns matching lines — could be many hits in decisions.jsonl. Risky but grep is cheap per line; decisions.jsonl might have time_remaining_s on every line → thousands of hits. Avoid. Grep reference/ first.
Actually wait — my own decisions.jsonl in data/private/ would show the exact obs structure I received! Each line is presumably the obs given to my agent. But it's 1MB+ and grepping "time_remaining" would hit every line. The grep tool returns "matching lines" — if every line matches, that's a flood. Hmm. But maybe lines are pretty-printed JSON? 1.3MB per match over ~600s... Let me not risk it.
Better: grep "time_remaining" in reference/ (small root). And RFL_RULES.md.
Let me also think: what if obs doesn't include time? The notice explicitly says "your `time_remaining_s` is the match clock and its meaning is unchanged" — so it exists in observations. I just need the exact key path. The reference implementation will show it.
Let me write the turn: brief prose + grep reference/ for time_remaining.
Actually — to save turns, grep pattern "time_remaining" path "reference/" — if the sample team uses it, great. If zero hits, next turn grep data/RFL_RULES.md.
Let me go.
m7 confirmed as the same latency disease as m11 (their flash-lite: 437 decisions at ~1.9s; our luna: 133 at ~2.5s, 206 deadlines missed between us) — the switch already made treats it, so no tactical rework needed there. Tonight goes to the buzzer rule: matches 17–20 reward shooting in the final seconds of each half and punish a loose ball near our own goal at the buzzer. I need clock-awareness in the shell, and first I need the exact observation field for the clock — checking the reference implementation.
grepreference/
The league answered107 characters
[grep reference/ /time_remaining/] no matches for /time_remaining/ in reference (8 file(s) searched) (0.1s)
Thought for 1,833 words
Let me think about where I am. I've read the notices, the table (partially), m7's digest (confirmed latency disease, already treated by the flash-lite switch), and most of team.py. The grep for "time_remaining" in reference/ found nothing.
The buzzer rule is the big new thing: matches 17-20 (round 4) run under it. Key implications:
1. A shot struck in the last second of a half is worth taking — nothing can block it.
2. A ball loose in front of your own goal as the clock runs out is a danger — clear it before the buzzer.
3. The clock stops at the buzzer; second halves are now ~12s longer.
I need to know what observation field gives me the clock. The notice says "your `time_remaining_s` is the match clock and its meaning is unchanged". So the field is `time_remaining_s` — presumably in obs somewhere. Let me check the SDK or the reference for the observation structure. The grep on reference/ found nothing for "time_remaining". Maybe it's in gauntlet.rfl_sdk — but I can't read that directly? Actually I can try grep in data/ or reference/. Let me check what the observation contains — maybe grep for "time_remaining" in data/ (rules file) or check the SDK.
Actually, the notice explicitly says: "Your `time_remaining_s` is the match clock and its meaning is unchanged". So the field name is `time_remaining_s`. I need to find where it lives in obs. Let me grep the rules file and maybe my own decisions.jsonl for it. My decisions.jsonl contains the observations passed to decide() presumably — that would show the exact structure. Let me grep for "time_remaining" in data/seasons/s3/m7_singularity_united_frontier_glm/decisions.jsonl or the m3 one.
Actually the private decisions.jsonl is in the match dir. Let me grep for "time_remaining" in data/ — that would find the rules mention and maybe the obs structure.
Plan for this session:
1. Confirm obs field for clock (grep data/ for time_remaining).
2. Add buzzer-awareness to team.py:
- In the last N seconds of a half (say ≤ 8s? The ball rolls 5-10s after buzzer, so a shot struck even at the buzzer counts; but the robot must strike before power cut — so strike while there's still time, e.g. last 10s: if presser has ball within kick range, kick at goal immediately, no model call needed — shell override).
- Danger case: ball loose near own goal in the last seconds — clear it hard away (kick toward opponent half / touchlines) rather than trying to build play.
- Also: after buzzer nothing matters (no decisions taken), so no code needed there.
3. Also consider: the second half is 12s longer — nothing to change, just awareness.
Implementation sketch in decide():
- Get clock: obs.get("time_remaining_s") or nested? Need to check structure. Maybe obs["clock"]["time_remaining_s"]? Let me grep my decisions.jsonl.
Also half detection: time_remaining_s presumably counts down to end of match (600s total, half at 300). If time_remaining_s > 300 we're in first half; the half ends when time_remaining_s hits 300 (first half) or 0 (second half). So "time left in half" = time_remaining_s - 300 if > 300 else time_remaining_s. But careful: does time_remaining_s reset per half or count the whole match? The notice says "Both halves are now exactly match_time_s / 2 of football" and "your time_remaining_s is the match clock". Hmm — "the clock STOPS at the buzzer and does not start again until play does — through the dead ball and through the interval after it". So the match clock runs 600s of football total; at the buzzer of half 1 the clock reads 300 and stops until second-half kickoff. So time_remaining_s ≤ 300 means second half; time to half buzzer = time_remaining_s - 300 in first half, time_remaining_s in second half.
Edge: if time_remaining_s is absent (older engine or practice?), fall back to no buzzer logic. Practice runs the current engine presumably with buzzers? Practice is "a REAL match (your current code vs a mirror of itself)" — probably runs the new rules. Good, practice will verify.
Buzzer logic design:
- LAST_SHOT_S = 10 (say). If time-to-buzzer ≤ 10 and we're the presser and ball within KICK_RANGE_M: kick at goal immediately (shell override, skip model call — saves latency too). Actually even better: within last ~10s, if presser and dist to ball ≤ kick range, kick at goal. If not in kick range, still go_to_ball (model call fine, or skip model and just go_to_ball to save latency? The model might pick a better target but with seconds left, getting to the ball and striking is the play).
- Danger clear: if time-to-buzzer ≤ 10 and ball is in our defensive third (near own goal, say within 3m of own goal line... own goal x is ±6.5? pitch 14x9 so goals at x=±7, X_LIMIT 6.5) and we're the presser and within kick range: kick AWAY — toward opponent goal corner / up the pitch, not a dribble. Actually kick_toward atk_goal from our own third is a clearance upfield — fine, that's the same action. But if the model would try to dribble, we override to kick. So: in the last seconds, presser within kick range ALWAYS kicks (at goal if in attacking areas, or upfield/away from own goal if deep). Simplest: kick toward a point far upfield in the opponent half, biased to a corner to avoid... actually kicking toward opponent goal from anywhere is a decent clearance and could be a goal. But from right in front of our own goal, kicking at the opponent goal centre is a long punt — fine.
Hmm, but one nuance: "A ball loose in front of your own goal as the clock runs out is a danger" — the cover robot should also be ready to clear? The cover robot stands on the ball→goal line 2m goal-side. If the ball is loose near our goal and the presser is far, the cover might be nearer. Our role assignment picks nearest as presser, so the cover becomes presser if nearer. OK.
Also: should the presser still call the model in the last 10s? Latency ~1.5s per call; with 10s left that's fine, but the model might choose dribble/walk_to instead of the shot. The notice says "A shot struck in the last second of a half is worth taking." So shell override: in final window, presser in kick range → kick at goal, no model call (also saves spend). Presser not in kick range → go_to_ball (no model call either — pure shell, zero latency, maximum urgency). That's clean and cheap.
What window? Ball rolls 5-10s after buzzer. A shot struck at t=1s before buzzer crosses during the window. But also a shot struck AT the buzzer — power cut mid-kick might not complete the kick. Safer: strike by ~2s before buzzer. Window of 10s: plenty to reach ball and strike if close; if far, go_to_ball and strike when in range. I'll use 10s.
Also the "hold the ball when clock nearly out" review point: "whether your players hold the ball when the clock is nearly out" — if we're leading and the ball is at our feet near the buzzer... holding the ball doesn't stop the buzzer; at the buzzer power cuts and the ball is loose with 5-10s of physics. If we're leading by 1 and the ball is at our feet in midfield, kicking it away (upfield, toward opponent corner) at the buzzer is safer than holding it (robot folds, ball rolls off randomly). Actually if we hold it, at power cut the robot folds and the ball... stays near a dead robot, probably fine. But a loose ball near OUR goal is the danger. If leading, in final seconds, if presser has ball in our defensive third, clear it long. If in opponent half, could just kick it at goal or into the corner — either is fine, ball far from our goal.
Simplest coherent policy for final window (≤10s to half buzzer), presser only:
- If within KICK_RANGE_M of ball: kick_toward atk_goal (from anywhere — it's a shot if in range, a clearance if deep). Hmm — from deep in our own corner, kicking at the opponent goal centre is a long ball up the middle; acceptable. But maybe better: if ball is in our defensive third, kick toward a far corner of the opponent half to keep it away from the middle where... actually opponent goal direction IS away from our goal. Kick at goal. Fine.
- Else: go_to_ball (no model call).
And cover robot unchanged (holds shape). Actually in the final window, should cover also push? If the presser is beaten and the ball is loose near our goal, cover is on the line — the role switch handles it (nearest presses). Keep it simple.
One more consideration: the model call skip in final window also reduces spend and latency — good.
Now, where does time_remaining_s live in obs? I must verify. Let me grep data/ for "time_remaining_s" — the rules file and my decisions.jsonl (which logs obs?) should show it. My decisions.jsonl is ~1.3MB per match; grep is cheap.
Also need to see the rest of team.py (truncated at _valid). I have the gist: _valid passes through go_to_ball/hold, and kick_toward/walk_to/turn_to with target validation. And build_team at the end which I haven't seen. I need to see the tail of team.py before editing. Let me read with offset. The file is maybe 8-10KB; the read truncated around _valid. Let me read from offset ~6000 or so. Actually the truncation happened mid-_valid. Let me read the rest.
Plan for next turns (I have 20 turns, 55 min, $2.38 left of session cap):
1. grep "time_remaining" in data/ (find obs structure + rules mention). Also maybe grep in my decisions.jsonl for the obs keys.
2. Read tail of team.py.
3. Edit team.py: add buzzer logic.
4. lint.
5. practice (1 run, ~$0.05-0.10).
6. Maybe adjust, practice #2 if needed.
7. note + done.
Budget-wise: fine. Let me do the grep now. Combine: grep "time_remaining" in data/ (whole root). That searches all files including big ones — grep returns matching lines only, cheap. But decisions.jsonl lines could be huge (each line a full obs+decision record?). A matching line could be enormous. Risky but grep returns "one line" — could be a 10KB line. Acceptable.
Actually, better: grep in data/RFL_RULES.md first for the field name and semantics, and grep my m3 decisions.jsonl for time_remaining to see the exact obs placement. Two greps = two turns. Or one grep on data/ root and see. Let me do grep on data/ root with pattern "time_remaining". If lines are huge, I'll cope.
Hmm, also the reference/ has no time_remaining — maybe the obs key is different, like "clock_s" or "t_remaining". The notice says "Your `time_remaining_s` is the match clock" — that strongly implies the obs field is literally time_remaining_s. Reference not having it is odd but reference is a sample, maybe minimal. Let me grep data/ to confirm.
Let me write the turn: brief prose + JSON grep.
The grep in reference/ came up empty, but the notice names the field explicitly — "your `time_remaining_s` is the match clock". I need to confirm exactly where it sits in the observation dict before I write clock-aware code against it. My own decisions.jsonl logs the observations we received, so a grep across data/ should show both the rules' wording and the live structure.
grepdata/
The league answered7,006 characters
[grep data/ /time_remaining/] 40 match(es) for /time_remaining/ in data (capped — narrow the pattern). Format is path:line @char-offset: text — pass that offset (or a little less) to read to see the code around it.
data/NOTICES.md:46 @2360: first half's 300. Your `time_remaining_s` is the match clock and its
data/RFL_RULES.md:95 @5092: obs["score"], obs["time_remaining_s"], obs["decision_interval_s"]
data/RFL_RULES.md:148 @8096: obs["score"], obs["time_remaining_s"], obs["decision_interval_s"]
data/gaffers/frontier_deepseek/night_000.md:493 @30335: obs["score"], obs["time_remaining_s"], obs["decision_interval_s"]
data/gaffers/frontier_deepseek/night_000.md:546 @33339: obs["score"], obs["time_remaining_s"], obs["decision_interval_s"]
data/gaffers/frontier_deepseek/night_004.md:497 @30486: obs["score"], obs["time_remaining_s"], obs["decision_interval_s"]
data/gaffers/frontier_deepseek/night_004.md:550 @33490: obs["score"], obs["time_remaining_s"], obs["decision_interval_s"]
data/gaffers/frontier_deepseek/night_008.md:2278 @92179: obs["score"], obs["time_remaining_s"], obs["decision_interval_s"]
data/gaffers/frontier_deepseek/night_008.md:2331 @95183: obs["score"], obs["time_remaining_s"], obs["decision_interval_s"]
data/gaffers/frontier_deepseek/night_008.md:2880 @132496: Alternative: implement decide() ourselves using rfl_sdk? The rules list gauntlet.rfl_sdk import allowed. Maybe skills only. Could write hand-written logic decid
data/gaffers/frontier_deepseek/night_008.md:3108 @156398: obs["score"], obs["time_remaining_s"], obs["decision_interval_s"]
data/gaffers/frontier_deepseek/night_008.md:3510 @190018: obs["score"], obs["time_remaining_s"], obs["decision_interval_s"]
data/gaffers/frontier_deepseek/night_008.md:3563 @193022: obs["score"], obs["time_remaining_s"], obs["decision_interval_s"]
data/gaffers/frontier_deepseek/night_008.md:3918 @213894: - obs provides detections: ball -> {forward_m, left_m, distance_m, bearing_deg, field_xy, seen_now, age_s}, teammates[], opponents[] same shape, self {field_xy,
data/gaffers/frontier_deepseek/night_008.md:4144 @234934: obs["score"], obs["time_remaining_s"], obs["decision_interval_s"]
data/gaffers/frontier_deepseek/night_008.md:4197 @237938: obs["score"], obs["time_remaining_s"], obs["decision_interval_s"]
data/gaffers/frontier_deepseek/night_008.md:4487 @254523: - obs keys: detections (ball/teammates/opponents with field_xy, forward_m, left_m, distance_m, bearing_deg, seen_now, age_s), self (field_xy, heading_rad, veloc
data/gaffers/frontier_deepseek/night_009.md:2975 @122538: obs["score"], obs["time_remaining_s"], obs["decision_interval_s"]
data/gaffers/frontier_deepseek/night_009.md:3028 @125542: obs["score"], obs["time_remaining_s"], obs["decision_interval_s"]
data/gaffers/frontier_deepseek/night_009.md:6041 @256665: obs["score"], obs["time_remaining_s"], obs["decision_interval_s"]
data/gaffers/frontier_deepseek/night_009.md:6094 @259669: obs["score"], obs["time_remaining_s"], obs["decision_interval_s"]
data/gaffers/frontier_deepseek/night_009.md:7688 @308451: obs["score"], obs["time_remaining_s"], obs["decision_interval_s"]
data/gaffers/frontier_fable/night_007.md:1137 @38964: [read data/private/s0/m3_frontier_fable_frontier_gemini/decisions.jsonl] {"robot": 0, "t": 0.5, "obs": {"time_remaining_s": 600.0, "decision_interval_s": 2.0, "
data/gaffers/frontier_fable/night_007.md:1138 @40432: {"robot": 1, "t": 0.5, "obs": {"time_remaining_s": 600.0, "decision_interval_s": 2.0, "you": {"id": "r1", "number": 2, "team": "AFC Fable", "attack_goal_xy": [7
data/gaffers/frontier_fable/night_007.md:1139 @41822: {"robot": 2, "t": 0.5, "obs": {"time_remaining_s": 600.0, "decision_interval_s": 2.0, "you": {"id": "r2", "number": 1, "team": "Gemini Flash FC", "attack_goal_x
data/gaffers/frontier_fable/night_007.md:1140 @43195: {"robot": 3, "t": 0.5, "obs": {"time_remaining_s": 600.0, "decision_interval_s": 2.0, "you": {"id": "r3", "number": 2, "team": "Gemini Flash FC", "attack_goal_x
data/gaffers/frontier_fable/night_007.md:1141 @44574: {"robot": 0, "t": 2.0, "obs": {"time_remaining_s": 598.0, "decision_interval_s": 2.0, "you": {"id": "r0", "number": 1, "team": "AFC Fable", "attack_goal_xy": [7
data/gaffers/frontier_fable/night_007.md:1142 @46096: {"robot": 1, "t": 2.0, "obs": {"time_remaining_s": 598.0, "decision_interval_s": 2.0, "you": {"id": "r1", "number": 2, "team": "AFC Fable", "attack_goal_xy": [7
data/gaffers/frontier_fable/night_007.md:1143 @47626: {"robot": 2, "t": 2.0, "obs": {"time_remaining_s": 598.0, "decision_interval_s": 2.0, "you": {"id": "r2", "number": 1, "team": "Gemini Flash FC", "attack_goal_x
data/gaffers/frontier_fable/night_007.md:1144 @49019: {"robot": 3, "t": 2.0, "obs": {"time_remaining_s": 598.0, "decision_interval_s": 2.0, "you": {"id": "r3", "number": 2, "team": "Gemini Flash FC", "attack_goal_x
data/gaffers/frontier_fable/night_007.md:1145 @50410: {"robot": 0, "t": 4.0, "obs": {"time_remaining_s": 596.0, "decision_interval_s": 2.0, "you": {"id": "r0", "number": 1, "team": "AFC Fable", "attack_goal_xy": [7
data/gaffers/frontier_fable/night_007.md:1146 @51797: {"robot": 1, "t": 4.0, "obs": {"time_remaining_s": 596.0, "decision_interval_s": 2.0, "you": {"id": "r1", "number": 2, "team": "AFC Fable", "attack_goal_xy": [7
data/gaffers/frontier_fable/night_007.md:1147 @52989: {"robot": 2, "t": 4.0, "obs": {"time_remaining_s": 596.0, "decision_interval_s": 2.0, "you": {"id": "r2", "number": 1, "team": "Gemini Flash FC", "attack_goal_x
data/gaffers/frontier_fable/night_007.md:1148 @54483: {"robot": 3, "t": 4.0, "obs": {"time_remaining_s": 596.0, "decision_interval_s": 2.0, "you": {"id": "r3", "number": 2, "team": "Gemini Flash FC", "attack_goal_x
data/gaffers/frontier_fable/night_007.md:1149 @55979: {"robot": 0, "t": 6.0, "obs": {"time_remaining_s": 594.0, "decision_interval_s": 2.0, "you": {"id": "r0", "number": 1, "team": "AFC Fable", "attack_goal_xy": [7
data/gaffers/frontier_fable/night_007.md:1150 @57392: {"robot": 2, "t": 6.0, "obs": {"time_remaining_s": 594.0, "decision_interval_s": 2.0, "you": {"id": "r2", "number": 1, "team": "Gemini Flash FC", "attack_goal_x
data/gaffers/frontier_fable/night_007.md:1151 @58650: {"robot": 3, "t": 6.0, "obs": {"time_remaining_s": 594.0, "decision_interval_s": 2.0, "you": {"id": "r3", "number": 2, "team": "Gemini Flash FC", "attack_goal_x
data/gaffers/frontier_fable/night_007.md:1152 @60038: {"robot": 2, "t": 8.0, "obs": {"time_remaining_s": 592.0, "decision_interval_s": 2.0, "you": {"id": "r2", "number": 1, "team": "Gemini Flash FC", "attack_goal_x
data/gaffers/frontier_fable/night_007.md:1153 @61193: {"robot": 3, "t": 8.0, "obs": {"time_remaining_s": 592.0, "decision_interval_s": 2.0, "you": {"id": "r3", "number": 2, "team": "Gemini Flash FC", "attack_goal_x
data/gaffers/frontier_fable/night_007.md:1154 @62377: {"robot": 2, "t": 10.0, "obs": {"time_remaining_s": 590.0, "decision_interval_s": 2.0, "you": {"id": "r2", "number": 1, "team": "Gemini Flash FC", "attack_goal_
(2.6s)The league answered991 characters
model error (1/3): InternalServerError: Error code: 504 - {'type': 'https://developers.cloudflare.com/support/troubleshooting/http-status-codes/cloudflare-5xx-errors/error-504/', 'title': 'Error 504: Gateway time-out', 'status': 504, 'detail': 'The origin web server did not respond to Cloudflare within the allowed time. This typically means the origin is overloaded or a backend process is taking too long.', 'instance': 'a3775123ead563d7', 'error_code': 504, 'error_name': 'origin_gateway_timeout', 'error_category': 'origin', 'ray_id': 'a3775123ead563d7', 'timestamp': '2026-09-07T17:10:12Z', 'zone': 'api.aimlapi.com', 'cloudflare_error': True, 'retryable': True, 'retry_after': 120, 'owner_action_required': True, 'what_you_should_do': '**Wait and retry.** Back off for at least 120 seconds. If the error persists, the website operator should investigate long-running processes on the origin server.', 'footer': 'This error was generated by Cloudflare on behalf of the website owner.'}The league answered16 characters
backing off 120s
The league answered991 characters
model error (2/3): InternalServerError: Error code: 504 - {'type': 'https://developers.cloudflare.com/support/troubleshooting/http-status-codes/cloudflare-5xx-errors/error-504/', 'title': 'Error 504: Gateway time-out', 'status': 504, 'detail': 'The origin web server did not respond to Cloudflare within the allowed time. This typically means the origin is overloaded or a backend process is taking too long.', 'instance': 'a377609678d02050', 'error_code': 504, 'error_name': 'origin_gateway_timeout', 'error_category': 'origin', 'ray_id': 'a377609678d02050', 'timestamp': '2026-09-07T17:20:45Z', 'zone': 'api.aimlapi.com', 'cloudflare_error': True, 'retryable': True, 'retry_after': 120, 'owner_action_required': True, 'what_you_should_do': '**Wait and retry.** Back off for at least 120 seconds. If the error persists, the website operator should investigate long-running processes on the origin server.', 'footer': 'This error was generated by Cloudflare on behalf of the website owner.'}The league answered16 characters
backing off 120s
The league answered991 characters
model error (3/3): InternalServerError: Error code: 504 - {'type': 'https://developers.cloudflare.com/support/troubleshooting/http-status-codes/cloudflare-5xx-errors/error-504/', 'title': 'Error 504: Gateway time-out', 'status': 504, 'detail': 'The origin web server did not respond to Cloudflare within the allowed time. This typically means the origin is overloaded or a backend process is taking too long.', 'instance': 'a377700c89a8946b', 'error_code': 504, 'error_name': 'origin_gateway_timeout', 'error_category': 'origin', 'ray_id': 'a377700c89a8946b', 'timestamp': '2026-09-07T17:31:18Z', 'zone': 'api.aimlapi.com', 'cloudflare_error': True, 'retryable': True, 'retry_after': 120, 'owner_action_required': True, 'what_you_should_do': '**Wait and retry.** Back off for at least 120 seconds. If the error persists, the website operator should investigate long-running processes on the origin server.', 'footer': 'This error was generated by Cloudflare on behalf of the website owner.'}Session over. Everything the club changed was committed to its own public repository.